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Artificial intelligence is transforming industries worldwide, but nowhere is its impact more profound than in healthcare. As AI-driven automation advances, ensuring transparency, validation, accuracy, and implementation of AI ethical principles becomes paramount—especially in high-stakes fields like medical imaging.

February 17, 2025 — Geneva, Switzerland — Unilabs, a leading diagnostic services provider in Europe, announced the selection of AI solutions from Oxipit, a pioneering medical imaging AI company, to deploy solutions for chest X-rays throughout Unilabs’ European network. This partnership will see Oxipit’s AI solutions, ChestLink and ChestEye, integrated into Unilabs’ radiology workflows, streamlining chest X-ray reporting through automated triage and second-reading capabilities. The agreement covers the option to use these solutions within the entire Unilabs group in Europe, with the initial rollout starting in Portugal.

How can AI revolutionize radiology and address critical challenges in healthcare? In this compelling interview, Dr. Aditya Kale, a radiologist and medical algorithmic audit lead at University Hospital Birmingham (UHB), shares his experience leading the largest retrospective study in UK, which was conducted on Oxipit’s ChestLink AI solution. From tackling the NHS backlog in chest X-rays to redefining reporting efficiency and patient care, Dr. Kale unveils key findings and offers valuable perspectives on AI’s potential to transform radiology workflows. Dive in to discover the groundbreaking results, lessons learned, and what the future holds for autonomous AI in healthcare.

We reflect on the year Oxipit has had. Including experiencing significant growth in 2024, driven by the increasing demand for our autonomous AI solutions like ChestLink, ChestEye, and Quality, which help address the challenges of rising workloads and staff shortages in the radiology sector.

Leiden University Medical Centre (LUMC), a leading academic hospital in the Netherlands, faced the common challenges of increasing radiology workloads and the need for more efficient resource allocation. Like many healthcare institutions, LUMC realised that, despite being a tier 3 academic hospital, a significant percentage of specific radiological examinations showed no pathology findings, which represented a significant opportunity to optimise workflow and use its resources more effectively. For chest X-rays, one of the most commonly performed radiological examination, retrospective validation showed that between 40% – 50% of the X-rays contained no findings and thus could be characterized as normal X-rays.

In a recent interview, Peter Corscadden, CEO of Oxipit, discusses the transformative role of autonomous AI in radiology. Oxipit’s AI-driven tool, ChestLink, autonomously handles up to 40% of chest X-ray workflows, freeing radiologists to focus on complex cases. Corscadden highlights the technology’s potential to reduce the strain on radiologists, improve diagnostic accuracy, and tackle healthcare inequalities—particularly in underserved regions like Rwanda. Looking ahead, Oxipit aims to expand its innovative AI solutions to further shape the future of healthcare.

The landscape of radiology is undergoing a profound transformation. As someone who has been deeply involved in both clinical practice and the advancement of artificial intelligence in medical imaging, I've observed firsthand how Computer-Aided Detection (CAD) systems have evolved from simple assistance tools to increasingly sophisticated solutions. However, we're now standing at the threshold of an even more significant change: the emergence of autonomous AI systems in radiology.

CAD (Computed Aided Detection) AI, tools that support detection, triage and classification of medical image diagnoses, have been the focus of $5.6B investment in a bid to combat the myriad of pressures facing the medical imaging industry. Medical imaging service lines are struggling in the face of increasing procedure volumes, intensifying workforce shortages coupled with a fundamental need to do more with less resource. Evident by Royal College of Radiologists (RCR) 2023 clinical radiology workforce census report, that “the radiology workforce grew by 6.3% in 2023. Yet the rate of CT and MRI scans surged by 11% in the same timeframe.”

In a recent interview, Peter Corscadden, CEO of Oxipit, discusses the transformative role of autonomous AI in radiology. Oxipit’s AI-driven tool, ChestLink, autonomously handles up to 40% of chest X-ray workflows, freeing radiologists to focus on complex cases. Corscadden highlights the technology’s potential to reduce the strain on radiologists, improve diagnostic accuracy, and tackle healthcare inequalities—particularly in underserved regions like Rwanda. Looking ahead, Oxipit aims to expand its innovative AI solutions to further shape the future of healthcare.

The key highlights from the Oxipit team at this year's UKIO conference, highlighting the pivotal discussions on autonomous reporting in radiology.